Compressed sensing of ECG signal for wireless system with new fast iterative method

2015 ◽  
Vol 122 (3) ◽  
pp. 437-449 ◽  
Author(s):  
Israa Tawfic ◽  
Sema Kayhan
Keyword(s):  
Compressed Sensing ◽  
Iterative Method ◽  
Ecg Signal ◽  
Wireless System

scholarly journals A Case Study in Low-Complexity ECG Signal Encoding: How Compressing is Compressed Sensing?

2015 ◽  
Vol 22 (10) ◽  
pp. 1743-1747 ◽  
Author(s):  
Valerio Cambareri ◽  
Mauro Mangia ◽  
Fabio Pareschi ◽  
Riccardo Rovatti ◽  
Gianluca Setti
Keyword(s):  
Compressed Sensing ◽  
Low Complexity ◽  
Ecg Signal ◽  
Signal Encoding

Iterative method with inertial terms for nonexpansive mappings: applications to compressed sensing

2019 ◽  
Vol 83 (4) ◽  
pp. 1321-1347 ◽  
Author(s):  
Yekini Shehu ◽  
Olaniyi S. Iyiola ◽  
Ferdinard U. Ogbuisi
Keyword(s):  
Compressed Sensing ◽  
Iterative Method ◽  
Nonexpansive Mappings ◽  
Inertial Terms

Sparse-matrix-based compressed sensing for spectrum sensing in Flexible Wireless System

2012 ◽  
Author(s):  
Doohwan Lee ◽  
Yoshiyuki Kabashima ◽  
Koujin Takeda ◽  
Takayuki Yamada ◽  
Kazunori Akabane ◽  
...  
Keyword(s):  
Compressed Sensing ◽  
Spectrum Sensing ◽  
Sparse Matrix ◽  
Wireless System

scholarly journals Modified Block Compressed Sensing for Extraction of Fetal Electrocardiogram from Mother Electrocardiogram Using Block Compressed Sensing Based Guided FOCUSS and FAST-Independent Component

2021 ◽  
Vol 50 (1) ◽  
pp. 123-137
Author(s):  
Muhammad Tayyib Awan ◽  
Muhammad Amir ◽  
Sarmad Maqsood ◽  
Musyyab Yousufi ◽  
Suheel Abdullah ◽  
...  
Keyword(s):  
Compressed Sensing ◽  
Compression Ratio ◽  
Ecg Signal ◽  
High Compression Ratio ◽  
Sensing Matrix ◽  
Compression Technique ◽  
High Compression ◽  
Fetal Ecg ◽  
Block Compressed Sensing ◽  
Modified Block

Fetal ECG extraction from abdominal ECG is critical task for telemonitoring of fetus which require lot of understanding to the subject. Conventional source separation methods are not efficient enough to separate FECG from huge multichannel ECG. Thus use of compression technique is needed to compress and reconstruct ECG signal without any significant losses in quality of signal. Compressed sensing shows promising results for such tasks. However, current compressed sensing theory is not so far that successful due to the non-sparsity and strong noise contamination present in ECG signal. The proposed work explores the concept of block compressed sensing to reconstruct non-sparse FECG signal using GFOCUSS algorithm. The main objective of this paper is not only to successfully reconstruct the ECG signal but to efficiently separate FECG from abdominal ECG. The proposed algorithm is explained in very extensive manner for all experiments. The key feature of proposed method is, that it doesn’t affect the interdependence relation between multichannel ECG. The useof walsh sensing matrix made it possible to achieve high compression ratio. Experimental results shows that even at very high compression ratio, successful FECG reconstruction from raw ECG is possible. These results are validated using PSNR, SINR, and MSE. This shows the framework, compared to other algorithms such as current blocking CS algorithms, rackness CS algorithm and wavelet algorithms, can greatly reduce code execution time during data compression stage and achieve better reconstruction in terms of MSE, PSNR and SINR.

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